Application of enhanced oil recovery methods in Kazakhstan has been ongoing for decades alongside the continued discovery of new oil and gas fields in the Pre-Caspian Basin. The objective of this review is to provide an overview of the hydrocarbon reserves and production, and the status of the petroleum industry in Kazakhstan, with a focus on the EOR methods and projects being applied to recover those reserves. A summary of the specific EOR methods in use was prepared, and existing enhanced recovery projects in Kazakhstan were reviewed and their successes and challenges were investigated. The performance of these projects in the context of EOR performance indicators such as capillary number and mobility ratio, as well as operational and environmental issues, were examined. Recommendations for current and potential applications of EOR in Kazakhstan were also discussed. The widespread application of thermal EOR methods, in use for decades in Kazakhstan’s older fields, was found to be successful, with very favorable impacts on mobility ratio from the addition of thermal energy to the reservoirs. Miscible EOR methods in Kazakhstan have had more limited success, with some significant challenges due to high concentration of hydrogen sulfide in the injected gas. Polymer injection started in the late 1960s, achieving good results. A recent polymer injection pilot project has shown some promise, with a favorable impact on mobility ratio and oil production, although the project has not yet been expanded beyond two polymer injectors. These results indicate the huge potential of existing and future EOR projects. This review is the first compilation of Kazakhstan’s existing oil and gas reserves, production, and EOR project performance, and should be seen as a guide to the existing applications of EOR methods in Kazakhstan.

Based on stratigraphic variations of petrology, geochemistry (major, trace elements), and pyrite framboids, we study the sedimentary environment of siliceous rocks of the Wufeng Formation in Wuxi, Northeastern Chongqing, China. Coupled Al₂O₃/(Al₂O₃+Fe₂O₃), SiO₂/Al₂O₃, with Al-Fe-Mn values indicate that Wufeng Formation are deposited in a continental margin and influenced by detrital input. U_EF-Mo_EF and V/Cr-U/Th cross-plots suggest that the siliceous shale was formed in dysoxic to anoxic conditions. Redox proxies imply that the lower, the middle to upper, and the top part of the Wufeng sediments were deposited in an anoxic, dysoxic and oxic environment, respectively. Accordingly, the average size of pyrite framboids are gradually increased from bottom to top, showing that increased oxidisability. A complete vibratory third-order cycle of sea level fluctuations during the Wufeng deposition can be identified. During Wufeng to Longmaxi transition, the sedimentary environment exhibits a short-scale oscillatory pattern and was probably transformed from an outer shelf to inner shelf. Coupled multi-proxies are considered more reliable proxies for deciphering redox conditions in fine-grained sediment.

This paper analyses the physical models in “Kapitaniak M, Hamaneh VV, Chávez JP, Nandakumar K, Wiercigroch M. Unveiling complexity of drill-string vibrations: experiments and modelling. International Journal of Mechanical Sciences 2015; 101-102: 324-327”. The results are that the physical models described in the original paper are clearly incorrect. For the physical model used to explain the axial vibration on a drill string, using a lumped mass-axial spring with damping to model a long slender drill string is not advisable. For the physical model used to explain the torsional vibration on a drill string, using a torsional spring-pendulum with damping to model a long slender drill string is not advisable. The drill string should be constrained in the well bore. As an example, appropriate physical and mathematical models of drill string axial and torsional vibrations are recommended.

Drilling through active shale formations has been a challenging practice in the oil and gas industry for a long period of time, given the complexity of shale structure and its interaction with Water Based Muds (WBMs). Although there have been many additives and methodologies proposed for a safe drilling through shale formations using WBMs, little success has been reported to the application of these methods once tested under different field conditions. In this paper, a new WBM formulated by nanomaterials was proposed to stabilize active shale layers during drilling. A series of rheological, density, filtration loss, bentonite dispersion and shale recovery tests were conducted on the mud samples formulated by nanosilica and Nano Glass Flakes (NGFs). The results indicated that NGF, as a cheap but effective nanomaterial, is able to significantly reduce the flirtation loss without posing any significant impacts on the density and the rheology of WBMs. It also appeared that the bentonite molecules were incapable to either hydrate or disperse in the drilling fluid system in the presence of NGFs. It seems that NGFs can stabilize clay minerals and reduce the filtration loss as remarkably efficient additive, but caution must be taken to ensure that they are properly disperse in the WBMs.

The acoustic response characteristics of shales were investigated by the acoustic transmission experiment, which is the basis of solving geological and engineering problems using the seismic or logging information during the process of the exploration and development of shale gas reservoirs. Based on the theory of acoustic wave and the background of acoustic transmission experiment, the initial condition, vibration source condition, boundary condition and stability condition were constructed, and the numerical simulation of acoustic transmission experiment of shales were completed through Matlab programming. The results show that under the same bedding angle, the acoustic time and attenuation coefficient of shales shown positive correlation with the bedding density; whereas under the same bedding density, the variation laws of the acoustic time and the attenuation coefficient of shales were more complex with the change of the bedding angle, that is, the acoustic time and attenuation coefficient of shales increased first, then decreased and then increased again with the increase of the bedding angle.

In this paper, we study the state estimation of compressible single phase flow in compressible porous media. The initial pressure distribution is estimated according to discrete adjoint approach based on the collected well pressure data. The first-order Tykhonov regularization method is used to obtain reasonable estimation. By analyzing the optimality condition of estimation problem, the discrete adjoint state equation and discrete adjoint gradient are derived based on the numerical scheme of the continuous equations. A quasi-Newton numerical optimization method related to adjoint gradient is proposed to solve the estimation problem. The estimation results with different regularization coefficients are compared and analyzed by numerical experiments. The deviation between the estimated pressure obtained without regularization and the real pressure is large. Estimation result with smaller deviation and higher smoothness can be obtained through appropriate regularization coefficient. When the observation error is large, the observed values generated by the estimated pressure fit well with the real pressure.

A systematic model development for oil flow in quasi-3D (1D + 2D) is presented. Our approach provides a unified modeling scheme. Besides, additional terms are obtained, which allows for tubing area variation along the flow direction. The area variation can be modeled as analytic function or random fluctuation, as it could be the result of deposits or tubing internal surface roughness. The proposed approach can be used to obtain analytic solutions which provide physical insight into the phenomena under scrutiny, including the validation of software tools, sensor development and sensor placement. One starts from conservation laws as given by kinetic theory and applies the transverse averaging technique (TAT) to extract the one-dimensional approximation in formal grounds. To demonstrate its application, the steady-state Ramey’s model, the Hasan’s transient model and a simple two-phase model are generated from the obtained equations.

Being one of the most commonly performed EOR methods, polymer injection is used to increase the mobility ratio and decrease water relative permeability to allow the injected fluid to sweep more oil towards the production well. Before the polymer solution is injected into the reservoir through the injection wells, the process of polymer injection must be simulated using commercial numerical reservoir simulators. In order to be able to simulate the process, the viscosity behavior of the solution must be known. Therefore, a model is required to estimate the viscosity of the injected fluids versus shear rate and polymer concentration. In this study, a new mathematical function based on the power-law fluid equation is presented, which can be applied to predict the viscosity of SPAM solutions. The two required parameters of the power-law equation are obtained by fitting a power-law function to the viscosity-shear rate data. Samples in different polymer concentrations (using two SPAM polymers with different molecular weights) were prepared and their viscosity was measured against different shear rates. The results were fitted to the power-law equation and their corresponding power-law parameters were recorded. A mathematical function was introduced and tested for each parameter. The new functions combined with the power-law equation were used to estimate the viscosity of different polymer solutions with different SPAM concentrations. The results showed that the model is capable of estimating the viscosity with acceptable precision. Furthermore, it is applicable in various temperatures and water salinities.

Current interest in deep, low-permeability formations (<10 md) demands accelerated development of high-temperature hydraulic fracturing technologies. Conventional guar systems break down above 300 °F and require higher polymer loadings to maintain thermal stability. However, higher polymer loadings generate more residue and damage to the proppant pack and the formation. To resolve these problems, a variety of high-temperature stabilizers are added to enhance the thermal stability of these fracturing fluids at temperatures above 300 °F. The focus of this work is to: (1) identify those additives that best enhance temperature stability of fracturing fluids and (2) study the rheological influence of incorporating these additives on the fracturing fluid systems.

The experimental fracturing-fluid solutions were prepared at a total polymer concentration of 30 and 40 lb/1000 gal. Additives such as synthetic polymer, oxygen scavengers, crosslinkers, crosslinker delay additives, and pH buffers were examined in this work. Hydrated polymer solutions were crosslinked with a metallic crosslinker between 200 and 400 °F. Viscosity measurements were carried out in a high-pressure/high-temperature (HP/HT) rheometer to evaluate rheology and thermal stability.

Results show that adding a synthetic polymer and a crosslinker with the slowest reaction rate improves the fracturing fluid thermal stability. Of the three other additives tested, oxygen scavengers showed the greatest enhancement to thermal stability while pH buffers showed the least. Through the addition of high-temperature stabilizing additives, the fracturing fluid in this work was able to maintain a stable performance at temperatures up to 400 °F.

Maintaining the thermal stability of fracturing fluids at a lower polymer loading remains a challenge in the industry. This work proposes techniques that can be used to enhance the thermal stability of fracturing fluids. Deeper knowledge about these different techniques will allow for better additive development and application in the field.

Different methods of enhanced oil recovery have been used to produce trapped oil. One of these methods is carbonated water injection in which CO₂ contained water is injected in reservoirs in order to decrease free CO₂ injection mobility, increase water viscosity and store/remove produced greenhouse CO₂ gas safely. Another enhanced oil recovery method is smart water injection at which the ions in brine are modified in order to make controlled reactions with distributed ions on the surface of rock to cause more hydrocarbon recovery. Therefore, combination of these two methods may also have a great effect on enhancing oil recovery or may result in recovery factor less than each method used alone. In this paper hybrid smart carbonated water injection method is investigated to study its applicability in oil recovery using core flooding setup. The experimental core flooding setup was designed to perform different types of EOR methods for the sake of recovery comparison with the new hybrid method. The effect of both brine content and volume of CO₂ is determining in hybrid EOR assessment. The main findings of this work show that the hybrid smart carbonated water results in the highest recovery factor in comparison to the most well-known EOR methods for carbonate cores.

Determining the saturated vapor pressure (SVP) of LNG requires detailed thermodynamic calculations based on compositional data. Yet LNG compositions and SVPs evolve constantly for LNG stored in tanks. Moreover, the SVP of the LNG in a tank influences boil-off rates and tank pressure trends. In order to make improved tank pressure control decisions it would be beneficial for LNG tank operators to be made more constantly aware of the SVP of the LNG in a tank. Machine learning models that accurately estimate LNG SVP from density and temperature inputs offer the potential to provide such information. A dataset of five distinct, internationally traded LNG cargoes is compiled with 305 data records representing a range of temperature and density conditions. This can be used graphically to interpolate LNG SVP. However, two machine learning methods are applied to this dataset to automate the SVP predictions. A simple multi-layer perceptron artificial neural network (MLP-ANN) predicts SVP of the dataset with root mean square error (RMSE) = 6.34 kPaA and R² = 0.975. The transparent open-box learning network (TOB), a regression-free optimized data matching algorithm predicts SVP of the dataset with RMSE = 0.59 kPaA and R² = 0.999. When applied to infill unknown LNG compositions the superior TOB method achieves prediction accuracy of RMSE ~3kPaA and R² = 0.996. Predicting LNG SVP to this level of accuracy is beneficial for tank-pressure management decision making.

Underground natural gas storage (UNGS) is an important part of the natural gas supply system to ensure a balanced energy supply. The surface system, as an important part of the gas storage, undertakes the functions of gas injection and gas production of the gas storage, and its investment economy is of vital importance. In fact, the UNGS surface pipeline network has two-way injection and production characteristics, which is different from the one-way production characteristics of conventional oil&gas gathering and transportation systems. This paper takes the minimum investment of the pipeline network as the objective function, considers the gas injection and gas withdrawal flow conditions and esablishes a mixed integer non-linear programming model (MINLP) for the surface pipeline network of the UNGS to optimize its pipeline layout and diameter parameters. Constraints including the well affiliation, the number of stations, the gathering radius, the processing capacity and the flow/pressure equilibrium equations, are also taken into consideration. Taking an UNGS in China as an example, the results of the optimal structure and diameter of the pipeline network, as well as the pipe flow, node pressure, and maximum/minimum flowrate during gas injection and gas withdrawal are obtained. Finally, the effects of constraints such as processing capacity and radius on the structure layout and investment of the UNGS are analyzed, verifying the reliability and effectiveness of the model.